Definition
Assume an information retrieval (IR) system has recall R and precision P on a test document collection and an information need. The F-measure of the system is defined as the weighted harmonic mean of its precision and recall, that is, \(F = {1\over \alpha {1\over P}+(1-\alpha ) {1\over R}}\), where the weight α ∈ [0,1]. The balanced F-measure, commonly denoted as F 1 or just F, equally weighs precision and recall, which means α = 1∕2. The F 1 measure can be written as \({F}_{1} = {2PR\over P+R}\).
Key Points
The F-measure can be viewed as a compromise between recall and precision. It is high only when both recall and precision are high. It is equivalent to recall when α = 0 and precision when α = 1. The F-measure assumes values in the interval [0,1]. It is 0 when no relevant documents have been retrieved, and is 1 if all retrieved documents are relevant and all relevant documents have been retrieved.
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© 2009 Springer Science+Business Media, LLC
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Zhang, E., Zhang, Y. (2009). F-Measure. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_483
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DOI: https://doi.org/10.1007/978-0-387-39940-9_483
Publisher Name: Springer, Boston, MA
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